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NIHMS1933008-supplement-Supplementary data 1 (1)
This ScienceHub entry provides Associated Data (Supplementary data 1) from the published manuscript Comput Toxicol. 2023 Jan 25;25:100261. doi: 10.1016/j.comtox.2023.100261. Further availability of data, as stated in the manuscript, will be made available on request. This dataset is associated with the following publication: Romano, J., L. Mei, J. Senn, J. Moore, and H. Mortensen. Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data science. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 25: 100261, (2023).
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Wehmas et al. 94-04 Toxicol Sci: Datasets for manuscript
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Dataset includes overview text document (accepted version of manuscript) and tables, figures, and supplementary materials. Supplementary tables provide summary data underlying figures, as noted in the text. This dataset is associated with the following publication: Wehmas, L., A. Deangelo, S. Hester, B. Chorley, G. Carswell, G. Olson, M. George, J. Carter, S. Eldridge, A. Fisher, B. Vallanat, and C. Wood. Metabolic Disruption Early in Life is Associated With Latent Carcinogenic Activity of Dichloroacetic Acid in Mice. TOXICOLOGICAL SCIENCES. Society of Toxicology, 159(2): 354-365, (2017).
Dataset for ORD-033372: Biological Thresholds Derived from Common Measures in Rat Studies are Predictive of Liver Tumorigenic Chemicals
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Microarray experiments used in the study. This dataset is associated with the following publication: Corton, J., K. Korunes, J. Abedini, H. El-Masri, J. Brown, K. Friedman, Y. Liu, C. Martini, S. He, and J. Rooney. Thresholds Derived from Common Measures in Rat Studies are Predictive of Liver Tumorigenic Chemicals. TOXICOLOGIC PATHOLOGY. Society of Toxicology, RESTON, VA, 48(7): 857-874, (2020).
Dataset for ORD-033344: A Set of Six Gene Expression Biomarkers Identify Rat Liver Tumorigens in Short-Term Assays
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Microarray experiments used in the study. This dataset is associated with the following publication: Corton, J., T. Hill, J. Sutherland, J. Stevens, and J. Rooney. A Set of Six Gene Expression Biomarkers Identify Rat Liver Tumorigens in Short-Term Assays. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 177(1): 11-26, (2020).
Dataset for ORD-033373: Gene Expression Thresholds Are Predictive of Rat Liver Tumorigens in Short-Term Assays
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The microarray experiments used in the study. This dataset is associated with the following publication: Hill, T., J. Rooney, J. Abedini, H. El-Masri, C. Wood, and J. Corton. Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 177(1): 41-59, (2020).
Supporting data for Hill et al (doi:10.1093/toxsci/kfw195)
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Tables, Figures, and Supplemental Materials. This dataset is associated with the following publication: Hill III, T., M. Nelms, S. Edwards, M. Martin, R. Judson, C. Corton, and C. Wood. Negative Predictors of Carcinogenicity for Environmental Chemicals. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 155(1): 157-169, (2017).
Dataset used in ORD-035008 - A Set of Six Gene Expression Biomarkers and Their Thresholds Identify Rat Liver Tumorigens in Short-Term Assays
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The links provided include the DrugMatrix-Affymetrix study, the TG-GATES study, and the TempO-Seq S1500+ study. This dataset is associated with the following publication: Lewis, R., T. Hill III, and C. Corton. A set of six Gene expression biomarkers and their thresholds identify rat liver tumorigens in short-term assays. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 443: 152547, (2020).
Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization
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The supplemental information for this paper includes chemical-specific analytical methods, raw instrument data for chemical concentration analysis, processed data for experiments on intrinsic hepatic clearance (CLint -- metabolism) and chemical fraction unbound in the presence of human plasma protein (fup). Figures showing the curve fits for determining CLint are provided. Finally, all data were released publicly as HTTK R Package v1.10.1. This dataset is associated with the following publication: Wambaugh, J., B. Wetmore, C. Ring, C. Nicolas, R. Pearce, G. Honda, R. Dinallo, D. Angus, J. Gilbert, T. Sierra, A. Badrinarayanan, B. Snodgrass, A. Brockman, C. Strock, R. Setzer, and R. Thomas. Assessing Toxicokinetic Uncertainty and Variability in Risk Prioritization. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 172(2): 235-251, (2019).
Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data
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*********** Note to Josh Harrill- I don't have a copy of the final manuscript so could you please add the description of this dataset (just delete this comment and enter or cut and paste and then it should be ready to route by clicking on 'Submit for Review' button above) **********. This dataset is associated with the following publication: Nyffeler, J., D. Haggard, C. Willis, W. Setzer, R. Judson, K. Paul-Friedman, L. Everett, and J. Harrill. Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data. SLAS Discovery. SAGE Publications, THOUSAND OAKS, CA, USA, 26(2): 292-308, (2021).
Datasets used in RD-023418: Adverse Outcome Pathway-Driven Identification of Rat Hepatocarcinogens in Short-Term Assays
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Datasets used in RD-023418: Adverse Outcome Pathway-Driven Identification of Rat Hepatocarcinogens in Short-Term Assays. This dataset is associated with the following publication: Rooney, J., T. Hill, C. Qin, F. Sistare, and C. Corton. Adverse outcome pathway-driven identification of rat liver tumorigens in short-term assays. TOXICOLOGY AND APPLIED PHARMACOLOGY. Academic Press Incorporated, Orlando, FL, USA, 356: 99-113, (2018).
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